Anthropic researchers used Claude Mythos Preview to find new weaknesses in two cryptographic methods, the company said Tuesday, including one that is being considered by the National Institute of Standards and Technology for both traditional and quantum computing.  

In a blog post detailing the work, the frontier AI company called it a “substantial” research advancement, but also emphasized that neither flaw affects software now in use.

“The attacks described in these two papers are the strongest attacks we have found to date,” the company wrote in the post. 

One of the weaknesses found was in HAWK, a digital signature scheme under review by the NIST as part of a search for encryption methods that could survive attacks from quantum computers. Working with a human researcher, the AI system found a mathematical shortcut, known as a nontrivial automorphism, in the lattice structure (a complex mathematical grid underpinning its security) HAWK relies on.

The discovered weakness cuts HAWK’s effective key strength in half, meaning key sizes would need to double to keep the same level of security. Anthropic said that change would erase much of what made HAWK an appealing candidate in the first place.

Ellen Boehm, senior vice president of strategy and AI innovation at Keyfactor, a digital identity and cryptography management provider, told CyberScoop that research like Anthropic’s proves that the NIST PQC evaluation process is working. 

She also said the research “elevates the importance for organizations to have visibility of where cryptography sits inside their enterprise, what business systems and processes it’s connected to, and the need for PQC readiness, if they haven’t already built a plan.” 

The other flaw was found in a weakened version of the Advanced Encryption Standard, or AES, the cipher NIST adopted in 2001 and the most widely used method for scrambling data in transit. Working largely on its own, Mythos invented a mathematical shortcut dubbed the “Möbius Bridge.” While real-world encryption scrambles data through 10 sequential layers, or “rounds,” researchers regularly study a simplified seven-round test version to measure security margins. In previous theoretical attacks, codebreakers had to check 256 separate values against a memory table, but Mythos created a shortcut that eliminated that lookup process entirely.

Combined with other optimizations, this discovery made the strongest known theoretical attack against seven-round AES 200 to 800 times faster. The attack is purely theoretical: It requires an impossible amount of target data — over 400 octillion messages — and cannot touch the full 10-round encryption protecting everyday software. Additionally, Anthropic pointed out that real-world systems remain completely safe.

Anthropic said it followed standard disclosure practices, notifying HAWK’s designers in June and coordinating public release with a NIST mailing list, and briefing government and industry partners beforehand. It also worked with researchers at ETH Zurich, Tel Aviv University and the University of Haifa to build a shared testing tool, called CryptanalysisBench, meant to let other researchers measure how AI systems perform against a range of ciphers.

The findings come as frontier AI models are being deployed by cybersecurity researchers in order to find vulnerabilities in all kinds of software. In June, intelligence agencies in the Five Eyes alliance warned that advanced AI models capable of wreaking havoc in the cyber domain are “months away.” However, a recent report found that despite the avalanche of bugs being unearthed, the threat level across the internet has not materially changed. 

Anthropic said it expects the same AI capabilities eventually to be applied to systems already in wide use, raising a separate question it said it has not yet resolved: how researchers, companies and governments should respond if a language model uncovers a flaw in a cryptographic system that protects critical infrastructure.

“As we develop increasingly powerful cryptanalytic results, it would be prudent to consider how researchers should react if a language model were to discover vulnerabilities in cryptosystems where attacks do have an immediate real-world impact,” the company wrote. “We hope that our work here will help launch these conversations.” 

Boehm said work like Anthropic’s further shows that enterprises should not rest on their laurels with any facet of their security apparatus. 

“AI is becoming a powerful tool for many things, including software quality assurance, code development, and in this case cryptographic analysis,” she told CyberScoop. “As AI tools become more widely and continuously used, it just elevates the need for enterprises to treat their trust infrastructure in an ongoing, operational manner versus thinking of it as a static environment that only changes every few years as new cryptographic algorithms are released.”

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Post-quantum cryptography didn’t sneak up on the industry. 

For years, security teams, standards bodies, hyperscalers, and governments have been pointing at the same horizon: a cryptographically relevant quantum computer will, eventually, dismantle the public-key algorithms underpinning today’s enterprise security. The latest executive order doesn’t introduce a new threat. It codifies what the field has long understood, and attaches deadlines to it.

For CISOs, the framing shift matters. PQC is fundamentally a readiness problem, not a cryptography problem. Watching Google accelerate its quantum roadmap, or seeing federal agencies restructure their security architecture around PQC, makes the stakes impossible to ignore.” Boards are already asking: “How are we thinking about post-quantum transition today?” For most organizations, the gap between that question and a credible answer is wider than it should be.

The EO is unambiguous on scope. PQC has moved from a research effort to real policy, with deadlines, accountability structures, and direct consequences for federal agencies, contractors, critical infrastructure operators, and the broader private sector that supports them.

Federal high-value systems must transition key establishment to PQC by Dec. 31, 2030. Digital signatures will follow by Dec. 31, 2031.

Those dates may appear distant, but for anyone who has navigated an enterprise-scale security transformation, with the procurement cycles, architecture reviews, and organizational change management that entails, 2030 sits squarely inside current planning horizons. The window for orderly execution is already narrowing.

What makes that window even tighter is that the most immediate risk has nothing to do with deadlines. “Harvest Now, Decrypt Later” attacks are already operational. Nation-state adversaries are collecting encrypted data today and storing it until quantum capabilities are sufficient to decrypt it: intellectual property, health records, financial transactions, source code, government communications, and more. The encryption protecting that data right now is, functionally, a time-delayed vulnerability. Long-lived sensitive data may already be compromised in ways that won’t become visible for years.

The first step for CISOs is shifting from awareness to ownership.

PQC readiness cannot be delegated to individual application teams or treated as a future compliance checkbox. That approach will not survive given the EO’s accountability requirements. Every organization needs a point person: a program lead, a cross-functional steering committee, or a dedicated cryptographic risk office. Whatever the structure, it needs authority and a seat at the leadership table.

That ownership must span security, IT, infrastructure, engineering, product, legal, compliance, procurement, and business stakeholders. Cryptography is embedded across the entire enterprise: certificates, keys, protocols, APIs, hardware, cloud services, code-signing systems, identity infrastructure, third-party platforms. No single team has the bandwidth to address this alone. A cross-functional working group or Center of Excellence should be an organizational prerequisite as we move into the future.

Visibility is going to be critical, and this is where most organizations will find the largest gaps.

CISOs need a clear picture of where cryptography exists across their environment: which algorithms are in use, which systems depend on vulnerable cryptography, what data requires long-term confidentiality, and which business processes would be disrupted by migration. Without that inventory, risk assessment is guesswork, remediation is impossible, and demonstrating progress to regulators or boards becomes an exercise in speculation.

The principle is straightforward: you cannot protect what you cannot see.

Furthermore, a cryptographic inventory cannot be a static spreadsheet updated annually and then filed away. It needs to function as a living view of the organization’s trust infrastructure, covering certificates, keys, algorithms, libraries, protocols, signing systems, certificate authorities, HSMs, workloads, devices, and third-party dependencies. 

Once that visibility exists, prioritization follows from business impact. Systems protecting long-lived sensitive data, critical infrastructure, customer trust, software integrity, and regulated environments move first, with everything else sequenced accordingly.

Beyond visibility, CISOs need a roadmap aligned to the order’s milestones rather than aspirational planning documents that never translate into funded programs.

The 2030 key establishment deadline requires understanding every point where encryption and key exchange mechanisms operate across critical systems. The 2031 digital signatures deadline extends that challenge to software integrity, code signing, document signing, authentication, identity infrastructure, and long-term verification. This is a multi-year transformation program, and it warrants the same organizational rigor as any other enterprise-wide initiative of comparable scope.

That means three categories of dedicated resources. First, funding: PQC readiness cannot be absorbed into existing security budgets without displacing other priorities. It requires multi-year investment in discovery tooling, testing, migration execution, automation, and governance. Second, talent: organizations need cryptography expertise, enterprise architecture capability, PKI experience, risk management, compliance support, and program leadership, a combination already in short supply across the industry. Third, technology: discovery tools, certificate and key lifecycle automation, policy enforcement, reporting infrastructure, and the architectural capability for crypto-agility.

Crypto-agility is the long-term objective that makes this transition worth doing properly.

Organizations that treat PQC as a one-time algorithm swap will find themselves back in the same position when standards shift again. The quantum transition is occurring in parallel with the rise of AI, machine identities, autonomous systems, and increasingly complex digital ecosystems, all of which depend on cryptographic trust. Organizations that do not actively govern that trust infrastructure will struggle with AI security, software supply chain integrity, identity governance, and the compliance mandates that follow.

The order functions as a forcing mechanism, converting PQC from a future technical concern into a present-day leadership accountability. Three questions now define where an organization stands:

• Do we have a clear picture of where our cryptographic risk lives?
• Do we have a funded, sequenced migration plan that meets the order’s deadlines?
• Can we demonstrate that our trust infrastructure is agile enough to adapt as standards and threats continue to evolve?

The debate over precisely when quantum computing will be a reality is a distraction. Building the visibility, governance, funding, and automation required to move with confidence is where we need to be spending our collective time and effort.

CISOs have moved past the question of whether to act. The operative question is how far behind the organization already is, and how quickly it can transform cryptography from an invisible dependency into a managed, measurable, and adaptive system of trust. The organizations that begin that work now will be the ones with options when the deadlines arrive.

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Apple has released quantum-resistant cryptographic code and the mathematical verification tools it developed to prove the code’s correctness, making them publicly available for independent review and broader use across the industry.

The release includes implementations of two quantum-secure algorithms, ML-KEM and ML-DSA, along with the formal verification libraries and tools Apple created to validate their accuracy. The company also published detailed documentation of its verification methodology, which it describes as achieving the strongest known correctness results for any widely deployed production implementation of these algorithms.

The quantum-secure algorithms are integrated into corecrypto, Apple’s cryptographic library used across its operating systems. The library handles encryption, decryption, hashing, and digital signatures on over 2.5 billion active devices. Apple began deploying quantum-resistant encryption in iMessage in 2024 and has expanded the technology to VPN services and TLS networking protocols.

One of the tools released is the company’s Cryptol-to-Isabelle translator, which converts cryptographic models between formal languages, along with supporting libraries needed to reproduce the results. Formal verification uses mathematical proofs to show that code works correctly for all possible inputs. Apple translated its code into Cryptol, a formal language developed by Galois, then into Isabelle, a proof assistant from the University of Cambridge and The Technical University of Munich, to prove both matched the official standards. Apple has used Isabelle previously to verify hardware cryptographic components.

The verification process uncovered errors that conventional testing would have missed. Researchers found a missing computational step in the ML-DSA code that would have silently broken digital signatures. If this bug had reached production, messages in iMessage may have appeared authenticated when they actually weren’t, leaving users unaware their communications lacked proper security.

Even with these tools, Apple acknowledged that it still depends on conventional cryptographic testing and evaluation is needed for assurance. Formal verification can catch errors that traditional testing simply cannot find. Testing works by trying many scenarios, but with complex cryptographic code, there are too many possible inputs to test exhaustively. Subtle bugs can hide in the gaps between test cases and never trigger a warning. Formal verification, by contrast, uses mathematics to prove correctness across all possible inputs at once.

However, Apple’s team writes that it couldn’t formally verify every single aspect of their code with the tools available, so they combined approaches: formal verification for core mathematical correctness, conventional testing for aspects formal methods couldn’t cover, and careful evaluation of how all the pieces work together. Apple argues this hybrid approach provides the most robust security for critical cryptographic software.

“Based on our work to date, we believe that the strongest assurance possible comes from combining formal verification with conventional methods and critically evaluating the end-to-end results,” the blog post reads.

Furthermore, the blog states that Apple selected ML-KEM and ML-DSA from among several standardized quantum-resistant algorithms because they best matched the company’s requirements for security, performance, and compact parameters. The algorithms address the threat posed by future quantum computers, which could potentially break the encryption methods currently protecting digital communications.

More information can be found on Apple’s corecrypto GitHub page. 

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